Making Sense of Open Government Data

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Abstract:, a major distributor of raw US government data, has published thousands of raw datasets on the Web for public access. While these datasets provide useful information, their potential has not yet been fully realized due to usability-related issues. In this work, we investigate potential ways to make sense of existing open government data using semantic web technologies. In our study, we demonstrate strategies for turning open government data into linked government data and present several case studies to illustrate the role of linked government data in making sense of government data.


DateCreated ByLink
July 15, 2011
James MichaelisDownload

Related Projects:

Inference Web Project LogoInference Web
Principal Investigator: Deborah L. McGuinness
Description: The Inference Web is a Semantic Web based knowledge provenance infrastructure that supports interoperable explanations of sources, assumptions, learned information, and answers as an enabler for trust. Provenance - if users (humans and agents) are to use and integrate data from unknown, uncertain, or multiple sources, they need provenance metadata for evaluation Interoperability - more systems are using varied sources and multiple information manipulation engines, thus increasing interoperability requirements Explanation/Justification - if information has been manipulated (i.e., by sound deduction or by heuristic processes), information manipulation trace information should be available Trust - if some sources are more trustworthy than others, trust ratings are desired The Inference Web consists of two important components: Proof Markup Language (PML) Ontology - Semantic Web based representation for exchanging explanations including provenance information - annotating the sources of knowledge justification information - annotating the steps for deriving the conclusions or executing workflows trust information - annotating trustworthiness assertions about knowledge and sources IW Toolkit - Web-based and standalone tools that facilitate human users to browse, debug, explain, and abstract the knowledge encoded in PML.
DCO-DS LogoLinking Open Government Data (LOGD)
Principal Investigator: Deborah L. McGuinness and Jim Hendler
Description: The LOGD project investigates the role of Semantic Web technologies, especially Linked Data, in producing, enhancing and utilizing government data published on and other websites.

Related Research Areas:

Data Frameworks
Lead Professor: Peter Fox
Description: None.
Future Web
Lead Professor: Jim Hendler
Description: Since its inception the World Wide Web has changed the ways people work, play, communicate, collaborate, and educate. There is, however, a growing realization among researchers across a number of disciplines that without new research aimed at understanding the current, evolving and potential Web, we may be missing or delaying opportunities for new and revolutionary capabilities. To model the Web, it is necessary to understand the architectural principles that have provided for its growth. Looking into the future, to be sure that it supports the basic social values of trustworthiness, personal control over information, and respect for social boundaries, a research agenda must be pursued that targets the Web and its use as a primary focus of attention. This research requires powerful scientific and mathematical techniques from many disciplines to explore the modeling of the Web from network- and information- centric views.
Knowledge Provenance
Lead Professor: Deborah L. McGuinness
Description: Knowledge Provenance
Concepts: Provenance,